Abstract
The spatial epidemic dynamics of COVID-19 outbreak in Italy were modelled by means of an Object-Oriented Bayesian Network in order to explore the dependence relationships, in a static and a dynamic way, among the weekly incidence rate, the intensive care units occupancy rate and that of deaths. Following an autoregressive approach, both spatial and time components have been embedded in the model by means of spatial and time lagged variables. The model could be a valid instrument to support or validate policy makers’ decisions strategies.
All Keywords
【저자키워드】 Time series, Object-Oriented Bayesian Network, Spatial correlation, COVID-19 Italian outbreak, 【초록키워드】 Bayesian, intensive care unit, Italy, Epidemic, COVID-19 outbreak, incidence rate, network, deaths, Support, component, approach, occupancy rate, variables, 【제목키워드】 COVID-19, Bayesian, outbreak, network, Italian,
【저자키워드】 Time series, Object-Oriented Bayesian Network, Spatial correlation, COVID-19 Italian outbreak, 【초록키워드】 Bayesian, intensive care unit, Italy, Epidemic, COVID-19 outbreak, incidence rate, network, deaths, Support, component, approach, occupancy rate, variables, 【제목키워드】 COVID-19, Bayesian, outbreak, network, Italian,